Abstract
Abstract
AI chatbots are increasingly used for emotional support, often outside formal care. Emerging evidence suggests that generative systems may produce modest reductions in symptoms of depression and anxiety. Yet a change in symptoms alone does not clarify the nature of the process involved. This viewpoint argues that chatbot interactions may primarily operate through structured mirroring and self-reflection rather than through the intersubjective engagement that underpins therapeutic transformation. We propose an implementation-focused distinction between tools that support symptom regulation and engagement and interventions that aim at enduring psychological change, emphasizing the need to specify mechanisms, relational conditions, and appropriate care pathways. Conflating perceived support with psychological change risks redefining therapeutic standards around technological affordance rather than relational encounters. As AI chatbots become embedded in mental health ecosystems, conceptual clarity and digital emotional literacy are essential to ensure that innovation strengthens rather than replaces the relational foundations of care.